The easiest way to run reproducible simulations is to explicitly set the seed, using an integer, before each run. Then it's easy to put the random number generator into the same state again, e.g.:
for (sim.num in 1:100) {
set.seed(sim.num)
... run simulation ...
}If you can't do this, you can record the value of .Random.seed prior to the simulation, and then when you want to reproduce that simulation again, set .Random.seed to that value, e.g.:
> set.seed(1) > sample(1:100, 5) [1] 27 37 57 89 20 > sample(1:100, 5) [1] 90 94 65 62 6 > set.seed(1) > sample(1:100, 5) [1] 27 37 57 89 20 > saved.seed <- .Random.seed > sample(1:100, 5) [1] 90 94 65 62 6 > .Random.seed <- saved.seed > sample(1:100, 5) [1] 90 94 65 62 6 >
This is not guaranteed to work with all random-number generators; see the NOTE section in ?set.seed
-- Tony Plate
At Friday 09:50 AM 12/17/2004, Suzette Blanchard wrote:
Greetings,
I have a simulation of a nonlinear model that is failing. But it does not fail til way into the simulation. I would like to look at the run that is failing and maybe I could if I could capture the seed for the failing run. The help file on set.seed says you can do it but when I tried
rs<-.Random.seed print(paste("rs",rs,sep=" "))
I got 626 of them so I don't know how to identify the right one. Please can you help?
Thank you, Suzette
================================= Suzette Blanchard, Ph.D. UCSD-PPRU
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